AIMC Topic: Deep Learning

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A Respiratory Signal Monitoring Method Based on Dual-Pathway Deep Learning Networks in Image-Guided Robotic-Assisted Intervention System.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (IGRI) systems, are susceptible to disruptions in patients' respiratory rhythm due to factors such as pain and psychological distress.

A Spatial Registration Method Based on Point Cloud and Deep Learning for Augmented Reality Neurosurgical Navigation.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: In order to achieve spatial registration for surgical navigation, a spatial registration method based on point cloud and deep learning is proposed.

Hybrid of Deep Feature Extraction and Machine Learning Ensembles for Imbalanced Skin Cancer Datasets.

Experimental dermatology
Skin cancer remains one of the most common and deadly forms of cancer, necessitating accurate and early diagnosis to improve patient outcomes. In order to improve classification performance on unbalanced datasets, this study proposes a distinctive ap...

Mitigating epidemic spread in complex networks based on deep reinforcement learning.

Chaos (Woodbury, N.Y.)
Complex networks are susceptible to contagious cascades, underscoring the urgency for effective epidemic mitigation strategies. While physical quarantine is a proven mitigation measure for mitigation, it can lead to substantial economic repercussions...

Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers-Based Model.

Cancer medicine
BACKGROUND: Morphological and vascular characteristics of breast cancer can change during neoadjuvant chemotherapy (NAC). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-acquired pre- and mid-treatment quantitatively capture informatio...

Evaluating the Cumulative Benefit of Inspiratory CT, Expiratory CT, and Clinical Data for COPD Diagnosis and Staging through Deep Learning.

Radiology. Cardiothoracic imaging
Purpose To measure the benefit of single-phase CT, inspiratory-expiratory CT, and clinical data for convolutional neural network (CNN)-based chronic obstructive pulmonary disease (COPD) staging. Materials and Methods This retrospective study included...

Automated Segmentation of Fetal Intracranial Volume in Three-Dimensional Ultrasound Using Deep Learning: Identifying Sex Differences in Prenatal Brain Development.

Human brain mapping
The human brain undergoes major developmental changes during pregnancy. Three-dimensional (3D) ultrasound images allow for the opportunity to investigate typical prenatal brain development on a large scale. Transabdominal ultrasound can be challengin...

GD-Net: An Integrated Multimodal Information Model Based on Deep Learning for Cancer Outcome Prediction and Informative Feature Selection.

Journal of cellular and molecular medicine
Multimodal information provides valuable resources for cancer prognosis and survival prediction. However, the computational integration of this heterogeneous data information poses significant challenges due to the complex interactions between molecu...

State-of-the-Art Deep Learning CT Reconstruction Algorithms in Abdominal Imaging.

Radiographics : a review publication of the Radiological Society of North America, Inc
The implementation of deep neural networks has spurred the creation of deep learning reconstruction (DLR) CT algorithms. DLR CT techniques encompass a spectrum of deep learning-based methodologies that operate during the different steps of the image ...

A multimodal vision transformer for interpretable fusion of functional and structural neuroimaging data.

Human brain mapping
Multimodal neuroimaging is an emerging field that leverages multiple sources of information to diagnose specific brain disorders, especially when deep learning-based AI algorithms are applied. The successful combination of different brain imaging mod...